Method for predicting drilling axial force of carbon fiber reinforced composite material

Abstract

The invention relates to a method for predicting drilling axial force of a carbon fiber reinforced composite material. The method comprises the following steps: step 1, establishing a drilling three-dimensional finite element model of CFRPs; step 2, modeling and solving the weight index of each input parameter in the drilling model by adopting an extreme random forest regression algorithm based onmachine learning; and step 3, establishing a multilayer correction neural network model considering CFRPs material characteristics and input parameter initial weight indexes, and predicting the maximum drilling axial force. According to the method for predicting the drilling axial force of the carbon fiber reinforced composite material, the method can effectively solve the problems that the material failure standard adopted in a finite element model is greatly different from the material failure of an actual material, the overall prediction process is more time-consuming, the neural network model ignores the material parameters of the composite material, and the established training model is greatly different from the actual test result.

Description

technical field [0001] The invention relates to the technical field of drilling axial force prediction, in particular to a method for predicting the drilling axial force of carbon fiber reinforced composite materials. Background technique [0002] Carbon fiber reinforced composites (CFRPs) have higher strength-to-weight ratio and higher specific stiffness-to-weight ratio compared with metal materials. These excellent properties provide a basis for the use of CFRPs to manufacture advanced structures in the aerospace, aerospace and defense industries. When riveting components or structural maintenance in assembly production, drilling of structural parts is often encountered. During the drilling process, high-quality holes are the primary factor to ensure the accuracy of its assembly with other structural parts. Due to the inherent anisotropy and structural heterogeneity of CFRPs, the drilling process may cause various damages such as delamination, burrs, fiber pull-out, and th...

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Problems solved by technology

[0006] The purpose of the present invention is to provide a method for predicting the axial force of carbon fiber reinforced composite material drilling, which can effectively solve the problem that the material failure standard used in the finite element model is quite different from the material failure of the actual material, and the overall prediction process is time-consuming And the neural network model ignores the material parameters of composite materials, and there is a big difference between the established training model and the actual test results

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